Secure and Privacy Preserving Big Data Analytics Curriculum Development

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

Organizations own and generate massive amounts of data that can be analyzed to generate understanding on customers as well as optimize consumer services. Computation on Big Data may require massive computational resources and, while an organization may have the capability to carry-out these analyses, it may use a third-party service to outsource some computations to be cost-effective. In these cases, data may be transferred to a third-party service, giving rise to concerns associated with the trustworthiness of the third-party computational devices and the security of sensitive information. When a third-party server is used for computation, data inherently becomes available in untrusted environments, for example: to a hacker during data transmission, or to adversaries at the third-party location where the computation is performed. Data owners may need to protect their data, and require cryptographic guarantees about data security and integrity of computational output from these third-party services. The proposed project from the University of Texas at Dallas (UT Dallas) will address this need by developing an experimental education program for Big Data Security and Privacy (BDSP). The project will develop a set of laboratory exercises and course modules in BDSP that will be shared with academia, government and industry. Recent advancements in embedded hardware technology to support trusted execution environment (TEE) have generated exciting opportunities for research in the field of cloud computing, trusted data analytics, and applied cryptography. By protecting code and data within a secure region of computation, a cloud service can ensure confidentiality and integrity of data and computations. There is a need to establish a scientific foundation for data analytical models to leverage TEEs, evaluate their limitations, explore performance overhead, and analyze security implications such as side channels. The proposed project will generate a BDSP laboratory for students to carry out experimentation in trustworthy analytics. The results will be incorporated into several of the existing courses in Cyber Security at UT Dallas. In addition, the project will generate a capstone course in BDSP. The goal is to develop a skilled workforce in BDSP to securely analyze the vast amounts of data that are used to provide better services in government, industry and academia. Further, with the established Center for Engaging Women in Cyber Security at The University of Texas at Dallas, this project will encourage, motivate and provide opportunities for female and minority students in cyber security. The project will leverage the Center to recruit highly qualified female and minority students into the education program in BDSP.